Businesses are struggling to fully utilise artificial intelligence (AI) due to inadequate data strategies, according to a new report by MIT Technology Review Insights in collaboration with Snowflake.
The report titled 'Data Strategies for AI Leaders' reveals that 95% of organisations face challenges when implementing AI, despite high aspirations for its potential to transform operations and drive innovation. Only 22% of business leaders consider themselves 'very ready' to engage with AI technologies, and 78% report that weak data foundations limit their ability to maximise AI investments.
Many organisations hope AI can increase efficiency and productivity, with 72% of surveyed businesses aiming for this outcome. Additionally, 55% anticipate improved market competitiveness, and 47% expect more innovation in products and services. However, the shortfall in foundational data strategies is a significant barrier to realising these ambitions.
The research highlights that robust data infrastructures are vital, especially those utilising modern cloud data platforms. Such platforms can manage not only organisational data but also integrate vast amounts of previously inaccessible data sources, including unstructured data like videos and images. A direct correlation exists between an organisation's readiness to deploy AI and its success in addressing issues related to data scalability, silo integration, and governance challenges.
Deploying AI at scale poses additional difficulties. 95% of respondents indicated facing obstacles, with data governance, security, or privacy concerns cited by 59% as the most significant challenges. Data quality and timeliness were concerns for 53% of respondents, while 48% identified costs as a key issue. Although resourcing and investment present hurdles, the report notes that cost reductions are possible through the development of smaller, yet equally effective, large language models (LLMs) by enterprises.
Baris Gultekin, Head of AI at Snowflake, discussed the implications of the findings. He stated, "Many of today's organisations have big ambitions for generative AI: they are looking to reshape how they operate and what they sell. Our joint research shows that as organisations feel increasing urgency to deploy AI applications, they are realising that their data can help them deliver insights from previously untapped sources of information. A strong data foundation is at the core of generative AI capabilities, and business leaders need to move quickly to deal with concerns such as data security and cost, and establish the foundation they need to deliver on the promise of AI."
Companies that have advanced their data infrastructures are beginning to see the benefits of generative AI. Those rewards are linked to substantial investments in data foundations, which facilitate the integration of AI. Establishing comprehensive data practices is essential for businesses aiming to harness AI, involving the aggregation, storage, and accessibility of crucial data resources. Such investments ensure more powerful AI applications while reducing associated governance and security risks.
The report is based on a poll conducted in May 2024 by MIT Technology Review Insights, which surveyed 276 executives from a wide range of industries globally to assess their data foundations for generative AI and associated challenges.
